1. Preparation of Fine Particulate Emissions Inventories
Chapter 4 – Nonroad Mobile Sources
After this lesson, participants will be able to:
describe EPA’s NONROAD model
explain the approaches for estimating PM emissions from aircraft, commercial marine vessels, and locomotives
The discussion of EPA’s National Mobile Inventory Model presented in Chapter 3 is also applicable to the nonroad category, but will not be repeated.

2. Nonroad Mobile - Overview
Nonroad Categories Addressed
Engines included in EPA’s NONROAD model
Aircraft
Commercial Marine Vessels
Locomotives
This presentation will first address source categories that are included in the NONROAD model.
Other offroad engines not in NONROAD that we will cover include aircraft engines, commercial marine vessels, and locomotives. 2

3. NONROAD Model - Overview
EPA’s NONROAD Model
Emission Estimation Model for Most Types of Nonroad Engines
Differentiated by Equipment Type and Other Characteristics
Past, Present and Future Year Inventories
Stand Alone (No User Data Necessary)
EPA’s NONROAD model estimates emissions for most types of nonroad engines (excluding aircraft, commercial marine, and locomotives)
Nonroad engines differentiated by equipment type, size of engine and fuel type
NONROAD estimates inventories for historic years back to 1970 and future years up to 2050.
NONROAD is stand-alone in that no user data is necessary to run the model. However, the model does allow for user inputs. 3

4. NONROAD Model – Overview (cont’d)
SCCs (4-digit SCC denotes engine type)
2260xxxxxx 2-Stroke Gasoline
2265xxxxxx 4-Stroke Gasoline
2267xxxxxx Liquefied Petroleum Gasoline (LPG)
2268xxxxxx Compressed Natural Gas (CNG)
2270xxxxxx Diesel
Two exceptions:
2282xxxxxx Recreational Marine
2285xxxxxx Railroad Maintenance
This slide lists the source categories that are included in the NONROAD model.
The four-digit source classification code generally denotes the engine type, or fuel that is used in the nonroad equipment.
The four-digit SCC denotes the equipment type instead of engine type in two categories:
recreational marine, and
railroad maintenance. 4

5. NONROAD Model – Overview (cont’d)
Equipment Category (7-digit SCC denotes equipment)
Airport ground support
Agricultural
Construction
Industrial
Commercial
Residential/commercial
Lawn and garden
Logging
Recreational marine vessels
Recreational equipment
Oil field
Underground mining
Railway maintenance
There are 12 different equipment categories denoted by the seven-digit SCC in the NONROAD model.
Each category may have multiple applications that are specified at the 10-digit SCC level.
10-digit SCC generally denotes specific application within equipment category

6. NONROAD Model – Overview (cont’d)
Pollutants
PM10-PRI, PM2.5-PRI, CO, NOx, VOC, SO2, and CO2
PM10 and PM2.5 emission factors represent Primary PM
NH3 not a direct output of NONROAD, can be estimated based on fuel consumption and EPA emission factors derived from light-duty onroad vehicle emission measurements
Model estimates exhaust and evaporative VOC components
The pollutants included in the NONROAD model are PM10 and PM2.5 (representing primary PM ), CO, NOx, VOC, SO2 and CO2.
Although ammonia is not a direct output of the NONROAD model, it can be estimated from fuel consumption estimates.
These fuel consumption estimates come from the model and the EPA emission factors are derived from light-duty onroad vehicle emission measurements.
In addition to exhaust pollutants, the NONROAD model estimates evaporative VOC for the following components: Crankcase, spillage, vapor displacement, permeation, hot soak, running loss, and diurnal. 6

7. NONROAD Model Emission Equation
Iexh = Eexh  A  L  P  N
where: Iexh = Exhaust emissions, (ton/year)
Eexh = Exhaust emission factor, (ton/hp-hr)
A = Equipment activity, (hours/year)
L = Load factor, (proportion of rated power used
on average basis)
P = Average rated power for modeled engines, (hp)
N = Equipment population
The NONROAD model calculates exhaust emissions by assuming that they are dependent on equipment activity.
Measures of equipment activity used in the model include:
number of hours per year the equipment is used,
the load factor at which the engine is operating,
the average rate of horse power of the engine, and
the equipment population (i.e., how many pieces of equipment are in use).
These equipment activity measures are multiplied by emissions factors in tons per horsepower-hour to obtain emission estimates as shown by the equation on the slide. 7

8. NONROAD Model - Emission Equation (cont’d)
Emission Factors
Dependent on engine type and horsepower
Future year emission controls or standards reflected in emission factor value
PM10 assumed to be equivalent to total PM
For gasoline engines, PM2.5 = 0.92 * PM10
For diesel engines, PM2.5 = 0.97 * PM10
For LPG and CNG-fueled engines, PM2.5 = PM10
SO2, CO2, and evaporative VOC emissions based on fuel consumption
The emission factors are dependent on the engine type as well as the engine size, or horsepower.
Future year emission controls or standards are reflected in revised emission rates, so that as older engines are scrapped and new engines replace them, revised emission rates are applied to the new engines to reflect the standards that they need to meet.
In the NONROAD model:
PM10 is assumed to be equivalent to total PM and for gasoline and diesel engines
PM2.5 is assumed to be 0.92 times PM10 for gasoline engines
PM2.5 is assumed to be 0.97 times PM10 for diesel engines. This is an updated estimate (was equal to gasoline PM2.5 fraction), based on an analysis of size distribution data for diesel
engines conducted for the Clean Air Diesel Rulemaking.
all PM is assumed to be less than PM2.5 for liquefied petroleum gas and compressed natural gas engines
SO2, CO2 and evaporative VOC emissions are based on fuel consumption. 8

9. Geographic Allocation
County-level allocation of equipment population
National or state-level equipment populations from PSR or alternate sources, reported by equipment type (SCC) and horsepower range
Allocates populations to counties using surrogate indicators that correlate with nonroad activity for specific equipment types
Because there are no estimates of county level populations, the NONROAD model estimates those populations using surrogate indicators.
Using national or state level equipment populations (either by equipment type or horsepower range), the model allocates them to the county level by using surrogate indicators.
These indicators correlate with nonroad activity for a specific equipment type. For example, agricultural equipment populations are allocated to counties based on acres of harvested cropland reported by US Dept of Agriculture. 9

10. Temporal Allocation
NONROAD accounts for temporal variations in activity
Monthly activity profiles by equipment category according to 10 geographic regions
Typical weekday and weekend day activity profiles by equipment category; do not vary by region
The NONROAD model also accounts for temporal variations in activity.
The temporal profiles vary by month and depend on the equipment category and the geographic region of the country.
The model contains typical weekday and weekend day activity profiles by equipment category, however, those do not vary by region. 10

11. Relation of NONROAD to National Mobile Inventory Model (NMIM)
NMIM2008 incorporates NONROAD2008
Common pollutant inventories produced by each (i.e., HC, CO, CO2, NOx, PM, and SO2) will be the same, provided the same inputs are used
Unlike NONROAD2008, NMIM includes default county temperature and fuel data in a single database
Additional pollutants in NMIM include ammonia, HAPs, among others
Use NONROAD2008 if equipment populations, fuel consumption estimates, or output by model year required
How does one decide whether to use NONROAD or NMIM?
NMIM2008 incorporates NONROAD2008, so that common pollutant inventories produced by each (i.e., HC, CO, CO2, NOx, PM, and SO2) will be the same, provided the same inputs are used.
NMIM’s primary improvement over NONROAD2008 is the inclusion of all the required county temperature and fuel property data for the nation in a single database.
NMIM also contains additional pollutants, including ammonia, gaseous HAPs, PAHS, metals, dioxins, and furans.
NONROAD includes specialized reporting options not available in NMIM, including equipment populations, fuel consumption, and by-model-year output. 11

12. Improving Inputs
Specify local fuel characteristics and ambient temperatures
Replace NONROAD model default activity inputs with state or local inputs
Perform local survey
Obtain local information to improve geographic allocation indicators and temporal profiles
Suggested methods for improving EPA’s latest 2002 model results:
specify local fuel characteristics and the ambient temperatures specific to the area being modeled.
replace the NONROAD default activity inputs with state or local data, if possible.
It can be resource intensive to obtain reasonable estimates to replace the default values. To obtain this data, it would be necessary to perform a local survey of equipment owners and users.
Another way to improve the model results is to obtain local information to improve the geographic allocation (i.e., going from state to county). Obtaining local data used for the temporal profiles can also improve the model results. 12

13. Improving Inputs (cont’d)
Significant PM Fine Equipment Categories include:
Diesel construction
Diesel farm
Diesel industrial
Gasoline lawn and garden
Gasoline recreational marine
Another approach to improve the model results is to focus on priority categories and obtain better data for those categories.
For example, for fine PM, priority categories would be diesel construction, diesel farm, diesel industrial, gasoline lawn and garden, and gasoline recreational marine.
Pechan has assisted several State and local agencies in developing improved activity inputs for construction, agricultural, as well as recreational marine categories. 13

14. Resources http://www.epa.gov/otaq/nonrdmdl.htm
From this web site, there are links to:
Downloadable version of NONROAD2008 model
Documentation
User’s Guide
Technical Reports to describe the sources and development of all model default input values
The latest version of EPA’s NONROAD model can be accessed at the web address listed here.
This web site contains documentation, a user’s guide, as well as technical reports to describe the sources and development of all the default input values (e.g., equipment populations, geographic allocations, growth factors, and emission rates). 14

15. AIRCRAFT - Overview SCCs
– Commercial Aircraft
– General Aviation
– Air Taxis
– Military Aircraft
Activity Data – landing and take-off operations (LTOs)
Emission Factors – aircraft/engine-specific or fleet average
The SCCs representing the aircraft categories that have been historically reported in the NEI are listed here.
The activity data used for aircraft are known as a landing and takeoff operations, or LTO.
Emissions are estimated by applying emission factors to the LTO data that are either specific to an aircraft or engine type.
If the make-up of the aircraft fleet is unknown, fleet averages can be applied to the emission factors. 15

16. AIRCRAFT - Overview (cont’d)
Definitions of Aircraft Categories:
Commercial - Aircraft used for scheduled service to transport passengers, freight, or both
Air taxis - Smaller aircraft operating on a more limited basis to transport passengers and freight
General aviation - aircraft used on an unscheduled basis for recreational flying, personal transportation, and other activities, including business travel
Military aircraft - aircraft used to support military operations
This slide lists the definitions of the aircraft categories that have been historically reported in the NEI. 16

17. AIRCRAFT - Overview (cont’d)
Aircraft operations are defined by landing and take-off operation (LTO) cycles, consisting of five specific modes:
Approach
Taxi/idle‑in
Taxi/idle‑out
Take-off
Climb-out
The operation time in each of these modes (TIM) is dependent on the aircraft category, local meteorological conditions, and airport operational considerations
The LTO cycle consists of different modes including: the approach, taxi idle in, taxi idle out, take off, and climb out.
Operation time in each of these modes is dependent on the aircraft category, meteorological conditions, as well as how the airport is operating (e.g., the length of time waiting to take off).
There can be substantial variations in these modes from airport to airport. Because different emission rates result when the aircraft are operating in each of these modes, it is important to consider all of these factors in estimating emissions from aircraft. 17

18. COMMERCIAL AIRCRAFT - NEI Method
Activity/Emissions Developed at Airport Level
Commercial Aircraft Activity
LTO data based in part on departures by aircraft type collected by Bureau of Transportation Statistics for U.S. carriers operating nonstop between domestic airports
T-100 Segment Data
LTO data reported by FAA for smaller commercial airports are also used and reconciled with T-100 data to avoid double counting
For the NEI, emissions are estimated for commercial aircraft by first compiling airport-level FAA LTO data by aircraft type  
- The aircraft in the BTS T-100 data is matched to aircraft in the FAA's Emission and Dispersion Modeling System (EDMS). For smaller airports, all airports included in the FAA's Terminal Area Forecast (TAF) data and data developed by OTAQ for airports that submit FAA form 5010 are also added to EDMS. Facilities that are accounted for in both the T-100, TAF, and 5010 data files are identified, to eliminate double counting. 18

19. COMMERCIAL AIRCRAFT - NEI Method (cont’d)
Activity/Emissions Developed at Airport Level
Commercial Aircraft Emissions
Emissions calculated using airport-level LTO data by aircraft type and emission rates from FAA’s Emissions and Dispersion Modeling System (EDMS) Version 5.1.
Used default engines for each aircraft type and default time-in-mode values.
EPA also using EDMS to estimate aircraft ground support equipment (GSE) and auxiliary power units
Will subtract out aircraft GSE from the NONROAD model estimates
Activity data is used with emission rates from the FAA’s Emissions and Dispersion Modeling System version As such, emissions already reported by airport/county, so no spatial allocation procedures required.
EDMS assigns default engine assignments for each aircraft type and default time-in-mode values – these defaults were used in the NEI calculations.
EPA also plans to use EDMS for developing emission estimates for aircraft ground support equipment and auxiliary power units.
Aircraft GSE emissions also estimated by NONROAD. However, EDMS has been identified as the preferred method for this category, since it is believed to be more accurate than NONROAD. Therefore, where possible, States should also use EDMS over NONROAD when preparing aircraft GSE. Note that if NONROAD is used to model for GSE emissions, one would have to apportion the county-level emissions outputs to the specific airport point facilities, since EPA will not accept county-level emissions submittals for GSE. 19

20. COMMERCIAL AIRCRAFT - NEI Method (cont’d)
EDMS5.1 estimates both PM10 and PM2.5 emissions
Based on International Civil Aviation Organization’s (ICAO) First Order Approximation, version 3.0
Represents substantial enhancements over previous PM estimation methods
The current version of EDMS has the functionality to estimate both PM-10, and more recently PM-2.5 emissions.
PM values based on International Civil Aviation Organization’s (ICAO) First Order Approximation, version 3.0 emissions model.
Enhancements to previous method - estimates more representative volatile PM emissions based on sulfur conversion chemistry and condensed organic gases, and includes a predictive capability for non-volatile PM based on a relationship between mass and the smoke number (SN) reported in the ICAO Engine Emissions Databank. 20

21. General Aviation and Air Taxi – NEI Method
National Emissions for General Aviation and Air Taxis are calculated using equation:
National Emissionsc,p = National LTOsc  EFc,p
where: LTOs = landing and take-off operations
EF = emission factor
c = aircraft category
p = criteria pollutant
EPA not currently estimating emissions for Military Aircraft
The NEI estimated emissions from the general aviation and air taxi categories by also using national LTO data available from FAA’s Terminal Area Forecasts and FAA Form 5010 LTO data compiled by OTAQ.
However, data are not available for specific aircraft types within each of the aircraft categories.
Consequently, emissions for these two categories were estimated by multiplying total LTO by an emission factor as shown in the equation on this slide.
EPA is currently not estimating default emissions for Military Aircraft. 21

22. General Aviation and Air Taxi – NEI Method (cont’d)
National Emissions Allocation
Airport Emissionsc,p,x = National Emissionsc,p  AFc,p,x
where: AF = allocation factor
x = airport (e.g., La Guardia)
c = aircraft category
p = criteria pollutant
AFc,x = LTOsc,x/National LTOsc
Once national emissions are calculated for general aviation and air taxi categories, the NEI allocates them to the county level based on airport level LTO data as shown by this equation.
Using La Guardia airport as an example, the NEI assumes that a fraction of the total LTO is assigned to La Guardia, and the emissions calculated from this allocation are assigned to the corresponding county. 22

23. General Aviation and Air Taxi – NEI Method (cont’d)
EPA developing a nationwide lead (Pb) emissions inventory from in-flight aircraft
In-flight emissions occur outside the landing and take-off cycle (above 3,000 feet)
Lead (Pb) emissions
Associated with General Aviation and Air Taxi categories
National aviation gas lead inventory allocated to airports based on percentage of piston-engine operations at each airport
Due to the need to include all emissions of lead in the NEI, EPA is developing a nationwide inventory of lead (Pb) from in-flight aircraft using aviation gasoline.
In-flight emissions are defined as emissions that occur outside the landing and take-off cycle, which is generally above 3,000 feet.
To calculate the national aviation gas (avgas) lead inventory, the volume of leaded avgas produced in the U.S. is multiplied by the concentration of Pb in the avgas (an average 2.12 grams/gallon) and by the fraction of Pb emitted from a combustion system operating on leaded fuel (0.75). To estimate lead Pb emissions for General Aviation and Air Taxi categories, a national lead (Pb) avgas inventory is allocated to individual airports based on the percentage of piston-engine operations for each aircraft type at each airport. 23

24. AIRCRAFT - NEI Method (cont’d)
Airport level emissions can now be reported as point source emissions associated with the airport’s latitude and longitude coordinates
Some airport locations may have more than one facility in the facility inventory
As all emissions are calculated at the airport level, these emissions can now be reported as point source emissions associated with the airport’s latitude and longitude coordinates.
Some airport locations may have more than one facility in the facility inventory. As long as the emissions are not duplicated, this is permissible. 24

25. AIRCRAFT - NEI Method (cont’d)
Information on the procedures used to develop criteria pollutant (as well as HAP) aircraft emission estimates will be made available at:
More information, as it is made available to the public, on the NEI methodology for estimating emissions from aircraft categories can be found at the web address listed here. 25

26. AIRCRAFT - General Approach
Determine the mixing height to be used to define the LTO cycle
Define the fleet make‑up for each airport
Determine airport activity in terms of the number of LTOs by aircraft/engine type
Select emission factors for each engine model associated with the aircraft fleet
Although it may be acceptable to rely upon the NEI data for smaller airports in an area, a bottom up inventory should be developed for the larger airports.
There are seven steps for developing an aircraft inventory for a specific airport:
Step 1 - Determine the mixing height to be used to define the LTO cycle. The mixing height is important because above the mixing height, emissions are not expected to contribute much to ground level pollutant concentrations.
Step 2 - Define the fleet make-up for the airport (i.e., types of aircraft).
Step 3 - Determine airport activity in terms of the number of LTO by aircraft and their associated engine-type.
Step 4 - Select emission factors for each engine model that is associated with the aircraft fleet at the airport being inventoried (instead of using defaults that EDMS may apply for a specific aircraft type). 26

27. AIRCRAFT - General Approach (cont’d)
Estimate the time-in-mode (TIM) for the aircraft fleet at each airport
Calculate emissions based on aircraft LTOs, emission factors for each aircraft engine model, and estimated aircraft TIM
Aggregate the emissions across aircraft
Step 5 – Estimate the time-in-mode for the aircraft fleet at the airport.
Step 6 – Calculate the emissions (based on the aircraft LTO data, the emission rates for each aircraft engine model, and the time-in-mode data).
Step 7 – Aggregate the emissions across aircraft to obtain a total for the airport. 27

28. COMMERCIAL AIRCRAFT - Improvements to NEI
Review the commercial airport data for representativeness
Determine engine types associated with local aircraft types, to replace default aircraft/engine assignments in EDMS
Obtain information on climb-out, takeoff, approach times, as well as taxi/idle times
Developing an emissions inventory for a local airport involves determining the engine types associated with the local aircraft types.
This data is an improvement over the assumptions used in the NEI for the commercial aircraft category.
In addition, developing information on climb-out, take-off, approach time, and taxi idle times will be an improvement over the defaults used in the NEI. 28

29. GA, AT and Military Aircraft - Improvements to NEI
Obtain local estimates of LTOs for these categories (to obtain LTOs not covered by FAA data)
Obtain information on the aircraft/engine types that comprise the aircraft fleet for these categories
Apply EPA engine-specific emission factors or EDMS
Include latitude/longitude of the airport
For the other categories (general aviation, air taxis, and military aircraft) the NEI can be improved by obtaining local LTO estimates, such as:
data from smaller airports that may not be reporting to the FAA
military bases (although heightened security measures have made it harder to obtain data from military operations). As mentioned earlier, EPA is not estimating military aircraft emissions for the 2008 NEI.
Another improvement is to obtain information on the aircraft/engine types that comprise the fleet for these other categories. If data on the mix of aircraft types in a fleet are available, engine specific emission factors or EDMS could be used to estimate emissions.
Finally, the NEI can be improved by maintaining the latitude/longitude of the airport so the emissions are not “smeared” across the entire county. 29

30. COMMERCIAL MARINE VESSELS - Overview
Commercial Marine Vessel SCCs
– Diesel, In Port
– Diesel, Underway
– Residual, In Port
– Residual, Underway
Diesel CMV consist of Category 1 and 2 engines
Residual CMV (steamships) consist of larger Category 3 engines
The SCCs representing the commercial marine vessel categories used in EPA’s default NEI are listed on this slide.
This includes activity for diesel ships in port and underway, as well as residual-fueled vessels or steamships for those two categories. 30

31. COMMERCIAL MARINE VESSELS - Overview
Emissions = Pop  HP  LF  ACT  EF
where: Pop = Vessel Population or Ship Calls
HP = Average Power (hp)
LF = Load Factor (fraction of available power)
ACT = Activity (hrs)
EF = Emission Factor (g/hp-hr)
This slide lists the equation for calculating emissions from commercial marine vessels.
It requires data on vessel populations, horsepower, load factor, and the time-in-mode operation. Emission factors in g/hp-hr are then applied to the calculated activity data to estimate emissions.
Applying this emission equation with these data will produce a better inventory. 31

32. COMMERCIAL MARINE VESSELS NEI Method – Category 1 & 2 CMV
National diesel emissions split into near-shore port and underway components
Per EPA SIP guidance, 75% of all diesel fuel consumed in port
Underway activity assigned to counties using ton-mile weighting factors developed from Bureau of Transportation Statistics GIS data
Port emissions assigned to 150 largest ports using port traffic data per Waterborne Commerce of the U.S.
Port emissions then assigned to a single county
The NEI methodology for Category 1 &2 commercial marine vessels is a top down method that splits national diesel emissions into port and underway components.
The methodology makes assumptions about what portion of the activity for both diesel and residual ships takes place in ports and what portion takes place underway (i.e., away from ports or on their way between ports).
These are allocated separately since port activity surrounds a port area, while underway covers a larger area such as along a river system. Both port and underway emissions are assigned to counties, however, port emissions are assigned to a single county in a port area. Historically, this is how the allocation has been performed – improvements to this allocation procedure are planned for the 2008 NEI. 32

33. COMMERCIAL MARINE VESSELS NEI Method – Category 3 CMV
Near port emissions based on two 1999 EPA studies:
Commercial Marine Activity for Deep Sea Ports in the United States
Commercial Marine Activity for Great Lake and Inland River Ports in the United States
These studies provide detailed activity profiles for typical ports, and provide method to extrapolate detailed time-in-mode activity data from a select typical port to another similar port
The NEI methodology used by EPA for Category 3 commercial marine vessels is different from Category 1 & 2.
In 1999 EPA completed the two studies shown here.
The content of these studies:
provides commercial marine activity profiles for select ports, and
presents a method for allocating detailed time-in-mode activity data from a typical port to another similar port. 33

34. COMMERCIAL MARINE VESSELS NEI Method – Category 3 CMV
Emission inventories developed for 117 ports for each mode of operation, including hotelling, maneuvering, reduced-speed zone, and cruising
Auxiliary engine and propulsion engine emissions estimated separately
Spatial allocation performed using GIS shapefiles to specify the geographic locations for each type of near port emissions
Hotelling and maneuvering emissions were assigned to the port point
Reduced-speed zone and cruise mode emissions were allocated to lines representing shipping lanes
EPA developed Category 3 inventories for a total of 117 deep sea and inland ports. Accounted for 4 different types of near-port emissions, including hotelling, maneuvering, reduced-speed zone, and cruise mode.
An improvement over previous inventories is that auxiliary engine and propulsion engine emissions were estimated separately using distinct power ratings, load factors and emission factors.
EPA spatially allocated emissions using GIS shapefiles to specify the geographic locations for each type of near port emissions.
Point shapefiles representing the 117 ports were developed, where each port was modeled as a single point, and hotelling and maneuvering emissions were assigned to the port point.
Reduced-speed zone and cruise mode lanes were both modeled as line shapefiles, and these emissions were allocated to those lines. 34

35. COMMERCIAL MARINE VESSELS NEI Method – CMV
EPA developing a GIS shape file library using BTS data to better allocate Category 1 & 2 port emissions to counties, and also to better allocate underway emissions to line segments/counties
EPA also developing an offshore Federal waters CMV inventory, including emissions from ~2-10 miles, up to 200 miles offshore
For 2008 NEI, for Category 1 & 2 vessels, EPA working to develop GIS shape file library (based on Bureau of Transportation Statistics data) to better allocate port emissions to counties, and also to better allocate underway emissions to line segments/counties.
EPA also developing an offshore Federal waters CMV inventory, including emissions from ~2-10 miles, depending on the State, up to 200 miles offshore. States will not be able to replace these estimates for the 2008 NEI. 35

36. COMMERCIAL MARINE VESSELS - Emission Factors
Emission factors available on a horsepower-hours basis
EPA developing updated emission rates
As part of Category 3 Marine Diesel Rule
Recently coordinating with ARB and European studies
PM2.5-PRI = 0.92 * PM10-PRI emissions
Horsepower-based emission factors are available for use with activity data on the number and size of engines, and the hours of operation.
EPA has been performing studies to develop updated emission factors as part of their rulemaking activities, such as the Category 3 Marine Diesel Rule, and have more recently been consulting with ARB and International studies (e.g., Entec and Swedish Environmental Research Institute) to develop more representative emission rates.
PM2.5 is assumed to be 0.92 times PM10 for diesel CMV engines. Deemed more representative than NONROAD model’s assumption of 0.97 for diesel engines, since higher sulfur fuels in medium and slow speed engines would tend to produce larger particulates than high speed engines on low sulfur fuels 36

37. COMMERCIAL MARINE VESSELS - Emission Factors (cont’d)
PM10-PRI EFs for Category 1 and Category 2 Engines:
Engine Category
PM10 [g/kW-hr]
Category 1: <0.9 liters/cylinder
0.54
Category 1: l/cyl
0.47
Category 1: l/cyl
0.34
Category 1: 2.5 – 5.0 l/cyl
0.30
Category 2 ( l/cyl)
0.32
This table presents EPA recommended baseline PM10 emission factors for specific categories of commercial marine engines, on a gram per kilowatt-hour basis for Category 1 and Category 2 engines (i.e., small commercial marine vessel engines). Category 1 vessel emission rates vary depending on engine displacement.
New Category 1 engines are subject to Tier 2 PM emission standards (starting between 2004 and 2007) which will result in overall lower PM emissions. 37

38. COMMERCIAL MARINE VESSELS - Emission Factors (cont’d)
PM10-PRI EFs for Category 3 Engines (> 30 l/cylinder):
Values representative of West Coast Ports – other US ports have slightly higher PM emission rates due to higher sulfur levels in residual oil
Low-load adjustments factors developed by pollutant
Emission factor constant to about 20% load – below that, emissions increase as the load decreases
Engine: Vessel Type
PM10 [g/kW-hr]
Propulsion: All Vessel Types
1.4
Auxiliary Engine: Passenger
1.3
Auxiliary Engine: Other Ocean-Going Vessels
1.1
EPA recommended PM10 emission factors for the larger engines are listed in this table.
These factors are listed for propulsion engines and auxiliary engines. Auxiliary engine emission factors vary somewhat for passenger ships. Emission factors account for ratios of distillate versus residual fuel use by vessel type. For example, passenger ships have a higher emission rate because a larger percentage of passenger ships relative to other ships use residual fuel for their auxiliary engines.
The values in the slide represent PM-10 emission factors for West Coast Ports. For all other ports in the US, a slightly higher emission factor is assumed, since residual oil fuel sulfur levels are estimated to be higher for other ports compared to West Coast ports (2.7% compared to 2.5%).
An adjustment to the emission factor is needed at loads below 20%, since below this level, brake-specific fuel consumption increases (and therefore emissions increase) as the load approaches 0%. 38

39. COMMERCIAL MARINE VESSELS - NEI Method (cont’d)
Procedures documentation for criteria pollutant and HAP commercial marine emission estimates for Category 1 and 2 vessels available at:
ftp://ftp.epa.gov/EmisInventory/2002finalnei/documentation/mobile/2002nei_mobile_nonroad_methods.pdf.
For Category 3 vessels, see:
ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile/commercial_marine_vessels_2002 _and_2005.pdf.
More information on the NEI methodology for estimating emissions from the commercial marine vessel categories can be found at the web addresses listed here.
As the 2008 NEI is developed, additional documentation describing improvements from these methods will be available. 39

40. COMMERCIAL MARINE VESSELS - Improvements to NEI
Review 2008 NEI emission estimates for representativeness
Allocate port emissions to ports other than 150 largest
Obtain activity estimates at the local or state-level from Department of Transportation, Port Authority
One approach to improving NEI emission estimates for the commercial marine vessel category is to review the spatial allocation of commercial marine emissions included in the NEI.
Note that:
NEI examines port traffic for the 150 largest ports in the United States and only allocates those emissions.
Additional ports are not accounted for in the allocation method. Identifying smaller ports that are not accounted for in the NEI would be an improvement.
Another approach to improving the NEI results is to conduct a bottom-up inventory by obtaining activity estimates at the state or local level from the DOT or Port Authority. 40

41. COMMERCIAL MARINE VESSELS - Improvements to NEI (cont’d)
Local CMV Study Needs
Fuel consumption
Categories of vessels
Number and size (hp) of vessels in each category
Number of hours at each time-in-mode
Cruising
Reduced speed zone
Maneuvering
Hotelling
Data needed to conduct a bottom-up CMV study that would improve upon the NEI may include:
data on fuel consumption
data to define categories and characteristics of the vessels (number, size and horsepower in each category)
Similar to aircraft, there are different emission rates depending on the operating mode of the vessels, so data on the fraction of the time engines are spent in each of the four modes would also be an improvement. 41

42. LOCOMOTIVES - Overview
SCCs:
– Diesel Class I Line Haul
– Diesel Class II/III Line Haul
– Diesel Passenger (Amtrak)
– Diesel Commuter
– Diesel Switchyard Locomotives
The SCCs representing the locomotive categories that have been used in previous NEIs are listed on this slide.
This includes larger Class I line haul locomotives that travel through many states, as well as the smaller Class II and III line haul locomotives that tend to operate in a smaller area.
The NEI has also reported information on passenger Amtrak trains, commuter trains, and switchyard operations. 42

43. LOCOMOTIVES - Overview (cont’d)
EPA not developing default locomotive emission estimates for 2008 NEI
States are encouraged to submit both activity and emissions
Class I line-haul locomotives account for ~80 percent of fuel of all rail operations
EPA is currently not developing default locomotive emission estimates. For the 2008 NEI, EPA encourages States to submit both activity and emissions for locomotives, so that emissions for all pollutants can be calculated.
Important to focus on Class I operations, since Class I line-haul activities have been shown to be the predominant source of rail-related emissions, accounting for ~80% of fuel and emissions of all rail operations. 43

44. LOCOMOTIVES - Class I Line Haul Methods
Emissions calculated by multiplying the amount of fuel consumed by emission factors
Fuel consumption for inventory area estimated by dividing traffic density expressed in gross tons miles (GTM) by system-wide fuel consumption index (GTM/gal)
Traffic Density (GTM) can be obtained directly from the individual railroads or from Association of American Railroads
Fuel consumption index calculated by dividing the system-wide gross ton miles (GTM) by the system-wide fuel consumption (gal)
Adjustments can be applied to account for grade and train type
Latest Guidance published for SESARM by Sierra Research, June 2004.
For Class I line-haul locomotives, emissions are calculated by multiplying the amount of fuel consumed in the inventory area by pollutant-specific emission factors. This calculation is performed for each railroad and each pollutant. The results for each railroad are then summed to obtain the total Class I railroad emissions in the inventory area.
The total amount of fuel consumed for individual Class I railroads needs to be allocated to the inventory area. This is done by dividing the traffic density (expressed in Gross Ton Miles, or GTM) for each Class I railroad track segment within the inventory area by the system-wide fuel consumption index (expressed in Gross Ton Miles per gallon or GTM/gal) for that railroad. This process is repeated for each railroad.
For every track segment within a state, each Class I railroad maintains information on traffic density (GTM), length (miles), direction, and geographic location. This information can be obtained either directly from the individual railroads or from the Association of American Railroads.
The fuel consumption index (GTM/gal), for each Class I railroad is calculated by dividing the system-wide gross ton miles (GTM) by the system-wide fuel consumption (gal). Each Class I railroad is required to report these statistics each year to the Surface Transportation Board (STB) in an annual report entitled “R-1.” Actual fuel use in a local area may be different from the system-wide average. Grade and train type adjustment factors can be applied to the index to account for these factors.
The fleet average emission factors will be a function of calendar year. 44

45. LOCOMOTIVES - Class I Line Haul Methods - ERTAC
Eastern Research Technical Advisory Committee (ERTAC) working to develop a railroad emissions inventory
ERTAC Proposed Method
Use Federal Railroad Administration’s GIS data to construct link-level million gross tons per mile (MGT) data
Combined with Fuel Consumption Index, calculate link-based fuel consumption to better reflect how GTM are actually concentrated across rail line route miles
Limitation of link-level activity data
Confidentiality issues
Some MGT data represent multiple railroad links
EPA working with ERTAC to develop a link-level (single lengths of track), spatially and temporally allocated consolidated emissions inventory of railroad sources. The inventory will focus on Class I, II, and III line-haul emissions, rail yard locomotive, and possibly other uncharacterized yard source emissions, and commuter and passenger locomotive emissions. The primary goal of the ERTAC Rail project is to improve upon previous methods used to derive rail emissions.
ERTAC recommended methodology:
Using the Federal Railroad Administration’s (FRA) nationwide 1:100,000 scale Rail Lines GIS layer, it is possible to construct a complete inventory of Class I line haul emissions based on link-level million gross tons per mile (MGT) data.
System-wide line haul fuel consumption and gross ton mile data would be used to calculate the Railroad Fuel Consumption Index (RFCI) value for each railroad. This index value represents the number of gross tons per mile (GTM) produced per gallon of diesel fuel. To calculate the number of gallons of diesel fuel consumed per link, each link’s GTM per year (obtained by multiplying the link’s MGT by the link’s length in miles) would be divided by the appropriate railroad’s RFCI. The result is a link-based fuel consumption value expressed in gallons/year.
A limitation of using this activity data is some of the data obtained by from Class I rail companies is considered confidential. Need express permission from Class I railroads to use these data. Also, link-level data do not provided means to separate out individual MGT contributions for links operated by multiple railroad companies, and also from Amtrak and commuter passenger operations. 45

46. LOCOMOTIVES - Class I Line Haul Methods - ERTAC
Emission factors calculated by railroad carrier to reflect system-wide fleet mix
Activity applied to emission factors to estimate link-level emissions by pollutant
Emissions can be easily aggregated to either the county or state level
ERTAC Methodology:
Emission factors per pollutant (gm or tons/gal) will be calculated for each railroad carrier depending on its system-wide fleet mix (line-haul and switchers will be treated separately), likely based on Tier level certification.
Activity data would be applied to locomotive emission factors to determine link-level emissions by pollutant.
Due to the way the FRA Rail Lines dataset is constructed, with breaks (nodes) in the line segments at state and county boundaries, the estimates can be easily aggregated to either the county or state level. 46

47. LOCOMOTIVES - Other Line Haul
Class II and Class III Line-haul
Obtain estimates of system-wide fuel consumption for these railroads
Allocate to counties based on track mileage, as freight density typically not available
If fuel data not available, may estimate fuel by applying average fuel consumption factors to annual carload-mile data
Methodologies for estimating emissions for Class II and Class III rail lines have typically relied on estimates of systemwide fuel consumption, allocated to counties or subcounties based on length of track in miles.
For operators for which only annual carloads can be obtained, may estimate fuel using an average fuel consumption per car-mile factor. This factor would be developed from reported data for fuel , track mileage, and number of annual carloads, then could be applied to carload data for remaining rail lines. 47

48. LOCOMOTIVES - Other Line Haul (cont’d)
Commuter and Passenger Rail
Obtain estimates of system-wide fuel consumption for these rail lines
Allocate to counties based on estimates of train-miles traveled
Calculated by county using the number of trains, schedule for each train, and length of the route traveled
Account for rail lines that operate only electric cars for their entire route or for portions of their route
Similar to Class II/III rail companies, methodologies for estimating emissions for passenger and commuter rail lines have typically relied on estimates of systemwide fuel consumption, allocated to counties or subcounties based on estimates of train-miles traveled.
Need to consider that many passenger/commuter lines operate only electric cars for their entire route or for portions of their route. In cases where a portion of the lines were electric, one needs to account for this in allocating systemwide fuel consumption to counties 48

49. LOCOMOTIVES - Rail Yards
Rail yard methodologies
Estimate portion of total Class I fuel consumption used for switching operations
For a given rail yard, apply emission factors or fuel consumption to the number of switchers in operation, adjusting for operating less than 24 hours per day, 7 days per week
For the 2008 NEI, states encouraged to report rail yard emissions as point sources
Switchyard activity/emissions have historically been based on following methodologies.
Estimate portion of total Class I fuel consumption used for switching operations. Inventory preparers need to consider that rail yard activity also associated with Class II, and to a lesser degree, Class III short-line rail operations.
For a given rail yard, apply available emission factors or fuel consumption factors to the number of switchers in operation, adjusting for operating less than 24 hours per day, 7 days per week. For example, EPA guidance provides an estimate of 82,500 gallons diesel fuel consumed per year per switcher.
For the 2008 NEI, States are encouraged to report rail yard and/or switch yard emissions as point sources, if the location is known. 49

50. LOCOMOTIVES - Emission Factors
Year 2008 Fleet Average Emission Factors
Line Haul PM10 Emission Factors
Class I: lbs PM10/thousand gallon
Class II/III: lbs PM10/thousand gallon
Rail Yard PM10 Emission Factors
16.49 lbs PM10/thousand gallon
0.53 tons PM10/yard locomotive
PM2.5 = 0.97  PM10
Fleet-average emission PM emission factors for year 2008 recommended by SESARM guidance for the line haul and yard operations are listed on this slide. Due to changing emission standards for locomotives, emission factors are a function of calendar year.
Line haul emission calculations are typically fuel-based. For switchyard locomotives, if fuel used is not available, emissions may be determined based on number of locomotives used in yard operations and annual emissions per yard locomotive.
PM2.5 estimated to be 97% of PM10 emissions based on current studies by EPA. Source: Regulatory Impact Analysis: Control of Emissions of Air Pollution from Locomotive Engines and Category 1 & 2 Marine CI Engines, May 2008.

51. LOCOMOTIVES - Resources
Revised Inventory Guidance for Locomotive Emissions, SESARM, May 2004
Eastern Regional Technical Advisory Committee (ERTAC)
Resources include:
Revised Inventory Guidance prepared for SESARM in May 2004 available at the first listed link.
Second link is to ERTAC home page, which includes proposed methods and background materials for each rail inventory component.

52. LOCOMOTIVES - Case Study - Overview
Case Study: County-level Locomotive Inventory for Sedgwick County, KS
See Case Study Number 4-1
This case study describes the development of a county level locomotive inventory for Sedgwick County, Kansas.
Direct student to Case Study Number 4-1 and discuss it with the students. 52

53. LOCOMOTIVES - Case Study – Solution
Case Study: County-level Locomotive Inventory for Sedgwick County, KS
See Handout 4-1
Distribute the solutions (Handout 4-1) to the case study. Review each question with the students. Encourage discussion among the class. Ask each group to report on the questions that were assigned to them. Ask the other groups to critique their responses. 53